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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sorting for secreted molecule production using a biosensor-in-microdroplet approach

Significance The design–build–test cycle of metabolic engineering is swiftly becoming test limited owing to advances in DNA synthesis and library design. At the same time, improving extracellular production requires high-throughput studies to detect extracellular (not intracellular) content. Traditional approaches that utilize chromatography-based analysis or plate-based fluorescence assays are relatively throughput limited and require a high degree of liquid handling. These limitations are avoided here by creating a generalizable approach for small molecule production screening. Namely, this paradigm combines “off-the-shelf” biosensors with large library screening from producing cells in a cell-type agnostic manner.

Bowman, Emily K.↗
DOE OSTI2025

In silico λ-dynamics predicts protein binding specificities to modified RNAs

Abstract RNA modifications shape gene expression through a variety of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Peptoid-Based Nanosheets Exhibiting Broad Antiviral Activity Against Enveloped RNA Viruses

Enveloped RNA viruses, such as Influenza A (H1N1) and Sindbis virus, pose persistent global health threats due to their high mutation rates, efficient transmission, and frequent drug resistance. By mimicking host cell membrane receptors, multivalent virus inhibitors can block viral attachment, making them promising broad-spectrum antiviral agents. However, most of existing antivirals are often limited by strain specificity, short-lived efficacy, and toxicity. Here, we introduce a broad-spectrum antiviral platform based on highly tunable and biocompatible two-dimensional nanomembranes (2DNMs) self-assembled from amphiphilic peptoids, operating via a non-genomic, mutation-insensitive mechanism. By varying peptoid sequence, we design and synthesize over twenty different 2DNMs with various surface charge and high density of viral-attachment ligands (VALs). The self-assembled architecture of these stable 2DNMs provides cooperative noncovalent multivalent binding to virus particles that result in effective inhibition of viral infection. Screening of variants identified three leads that potently suppressed Influenza A (H1N1) and Sindbis virus infection across median tissue culture infectious dose (TCID50), plaque, RT–qPCR, and immunofluorescence assays, while maintaining >90% cell viability. These nanosheets significantly reduced infectious titers, viral RNA replication, and intracellular viral protein expression, indicating inhibition at early stages of viral entry and propagation. The sequence programmability, chemical robustness, and mutation-insensitive antiviral activity distinguish 2DNMs from traditional antivirals and positions them as a versatile materials platform for antiviral coatings, protective barriers, and prophylactic biomedical applications.

Influenza A virus↗
DOE OSTI2024

Automated AI-driven Molecular Design for Therapeutic Discovery

In recent years, artificial intelligence and machine learning (AI/ML) approaches have revolutionized the process of designing new therapeutics, enabling scientists to rapidly respond to emerging threats from various pathogens. A prime example is the SARS-CoV-2 main protease, a key target for the development of antiviral inhibitors. In this study, we employed a novel, integrated approach that combines AI-driven iterative design of inhibitor candidates, screening based on physio-chemical properties and toxicity, physics-based computational modeling of protein-inhibitor interactions, and AI-assisted analysis of Native MS biophysical assay and characterization of designed candidates. Our deep learning 3D-scaffold model, which uses an input scaffold as a starting point, generated tens of thousands of compounds while preserving the key scaffold. To optimize these candidates, we calculated a comprehensive set of 136 descriptors, including both 2D and 3D molecular features, for compounds targeting the SARS-CoV-2 Main protease (Mpro) and a neurodegenerative disease-associated protein, cyclophilin (Cyp). The generated compounds were initially filtered based on their properties and then ranked according to their predicted binding affinity using our automated modeling and ML methods. Experimental validation of the Mpro candidates showing inhibitory activity demonstrates that our workflow can expedite the therapeutic discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

3D Printing of Functional Hydrogel Devices for Screenings of Membrane Permeability and Selectivity

Developing a fundamental understanding of the effects of varying ligand chemistries on mass transport rates is key to designing membranes with solute-specific selectivity. While permeation cells offer a robust method to characterize membrane performance, they are limited to assessing a single membrane chemistry or salt solution per test. As a result, investigating the effects of varying ligand chemistries on membrane performance can be a tedious process, involving both the preparation of multiple samples and numerous, time-consuming permeation tests. This study uses digital light processing (DLP) 3D printing to fabricate a millifluidic flow-based permeation device made from a hydrogel active ester network that can be easily functionalized with ion-selective ligands. Without the need for bonding or assembly steps, ligands can be introduced and tested in the permeation device by simply injecting a small volume of a ligand solution. Various salt concentrations and molecular species can be cycled through a single device by switching the solution feeding into the salt reservoir, thereby reducing the number of samples needed for permeability and selectivity screenings. This research sets the groundwork for formulation development and postprocessing methods to 3D-print functional millifluidic devices capable of assessing solute selectivity in membranes and polymer adsorbents for aqueous separations. In this work, comparable salt permeability trends were observed with both 3D-printed devices and traditional assays. Devices were functionalized with an imidazole ligand to investigate salt permeability and selectivity of monovalent and divalent salts. Measurements showed increasing permeability for monovalent salts (NaCl) relative to divalent salts (MgCl 2 , CuCl 2 ) in functionalized membranes, with higher monovalent/divalent selectivity at increasing imidazole grafting densities. Here, the methods and findings described here represent a step toward developing higher-throughput methods with 3D-printed devices for screening the effects of ligand chemistry on mass transport rates in membrane materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Next-generation large-scale binary protein interaction network for Drosophila melanogaster

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the ‘FlyBi’ dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Intact mass spectrometry screening to optimize hydroxyl radical dose for protein footprinting

Hydroxyl radical protein footprinting (HRPF) using synchrotron radiation is a well-validated method to assess protein structure in the native solution state. In this method, X-ray radiolysis of water generates hydroxyl radicals that can react with solvent accessible side chains of proteins, with mass spectrometry used to detect the resulting labeled products. An ideal footprinting dose provides sufficient labeling to measure the structure but not so much as to influence the results. The optimization of hydroxyl radical dose is typically performed using an indirect Alexa488 fluorescence assay sensitive to hydroxyl radical concentration, but full evaluation of the experiment's outcome relies upon bottom-up liquid chromatography mass spectrometry (LC-MS) measurements to directly determine sites and extent of oxidative labeling at the peptide and protein level. A direct evaluation of the extent of labeling to provide direct and absolute measurements of dose and “safe” dose ranges in terms of, for example, average numbers of labels per protein, would provide immediate feedback on experimental outcomes prior to embarking on detailed LC-MS analyses. To this end, we describe an approach to integrate intact MS screening of labeled samples immediately following exposure, along with metrics to quantify the extent of observed labeling from the intact mass spectra. Intact MS results on the model protein lysozyme were evaluated in the context of Alexa488 assay results and a bottom-up LC-MS analysis of the same samples. In conclusion, this approach provides a basis for placing delivered hydroxyl radical dose metrics on firmer technical grounds for synchrotron X-ray footprinting of proteins, with explicit parameters to increase the likelihood of a productive experimental outcome. Further, the method directs approaches to provide absolute and direct dosimetry for all types of labeling for protein footprinting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An effective human uracil-DNA glycosylase inhibitor targets the open pre-catalytic active site conformation

Human uracil DNA-glycosylase (UDG) is the prototypic and first identified DNA glycosylase with a vital role in removing deaminated cytosine and incorporated uracil and 5-fluorouracil (5-FU) from DNA. UDG depletion sensitizes cells to high APOBEC3B deaminase and to pemetrexed (PEM) and floxuridine (5-FdU), which are toxic to tumor cells through incorporation of uracil and 5-FU into DNA. To identify small-molecule UDG inhibitors for pre-clinical evaluation, we optimized biochemical screening of a selected diversity collection of >3,000 small-molecules. We found aurintricarboxylic acid (ATA) as an inhibitor of purified UDG at an initial calculated IC 50 < 100 nM. Subsequent enzymatic assays confirmed effective ATA inhibition but with an IC50 of 700 nM and showed direct binding to the human UDG with a K D of <700 nM. ATA displays preferential, dose-dependent binding to purified human UDG compared to human 8-oxoguanine DNA glycosylase. ATA did not bind uracil-containing DNA at these concentrations. Yet, combined crystal structure and in silico docking results unveil ATA interactions with the DNA binding channel and uracil-binding pocket in an open, destabilized UDG conformation. Biologically relevant ATA inhibition of UDG was measured in cell lysates from human DLD1 colon cancer cells and in MCF-7 breast cancer cells using a host cell reactivation assay. Collective findings provide proof-of-principle for development of an ATA-based chemotype and “door stopper” strategy targeting inhibitor binding to a destabilized, open pre-catalytic glycosylase conformation that prevents active site closing for functional DNA binding and nucleotide flipping needed to excise altered bases in DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

PHOTO‐SENSITIVE LEAF ROLLING 1 encodes a polygalacturonase that modifies cell wall structure and drought tolerance in rice

Summary The biosynthesis and modification of cell wall composition and structure are controlled by hundreds of enzymes and have a direct consequence on plant growth and development. However, the majority of these enzymes has not been functionally characterised. Rice mutants with leaf‐rolling phenotypes were screened in a field. Phenotypic analysis under controlled conditions was performed for the selected mutant and the relevant gene was identified by map‐based cloning. Cell wall composition was analysed by glycome profiling assay. We identified a photo‐sensitive leaf rolling 1 ( psl1 ) mutant with ‘napping’ (midday depression of photosynthesis) phenotype and reduced growth. The PSL1 gene encodes a cell wall‐localised polygalacturonase (PG), a pectin‐degrading enzyme. psl1 with a 260‐bp deletion in its gene displayed leaf rolling in response to high light intensity and/or low humidity. Biochemical assays revealed PG activity of recombinant PSL1 protein. Significant modifications to cell wall composition in the psl1 mutant compared with the wild‐type plants were identified. Such modifications enhanced drought tolerance of the mutant plants by reducing water loss under osmotic stress and drought conditions. Taken together, PSL1 functions as a PG that modifies cell wall biosynthesis, plant development and drought tolerance in rice.

Zhang, Guangheng↗
DOE OSTI2023

Peptides from human BNIP5 and PXT1 and non-native binders of pro-apoptotic BAK can directly activate or inhibit BAK-mediated membrane permeabilization

Apoptosis is important for development and tissue homeostasis, and its dysregulation can lead to diseases, including cancer. As an apoptotic effector, BAK undergoes conformational changes that promote mitochondrial outer membrane disruption, leading to cell death. This is termed “activation” and can be induced by peptides from the human proteins BID, BIM, and PUMA. To identify additional peptides that can regulate BAK, we used computational protein design, yeast surface display screening, and structure-based energy scoring to identify 10 diverse new binders. We discovered peptides from the human proteins BNIP5 and PXT1 and three non-native peptides that activate BAK in liposome assays and induce cytochrome c release from mitochondria. Crystal structures and binding studies reveal a high degree of similarity among peptide activators and inhibitors, ruling out a simple function-determining property. Our results shed light on the vast peptide sequence space that can regulate BAK function and will guide the design of BAK-modulating tools and therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identifying Receptor Kinase Substrates Using an 8000 Peptide Kinase Client Library Enriched for Conserved Phosphorylation Sites

In eukaryotic organisms, protein kinases regulate diverse protein activities and signaling pathways through phosphorylation of specific protein substrates. Isolating and characterizing kinase substrates is vital for defining downstream signaling pathways. The kinase-client (KiC) assay is an in vitro synthetic peptide LC-MS/MS phosphorylation assay that has enabled identification of protein substrates (i.e., clients) for various protein kinases. For example, previous use of a 2100-member (2k) peptide library identified substrates for the extracellular ATP receptor-like kinase, P2K1. Many P2K1 clients were confirmed by additional in vitro and in planta studies, including integrin-linked kinase 4, for which we provide the evidence herein. In addition, we developed a new KiC peptide library containing 8000 (8k) peptides based on phosphorylation sites primarily from Arabidopsis thaliana datasets. The 8k peptides are enriched for sites with conservation in other angiosperm plants, with the paired goals of representing functionally conserved sites and usefulness for screening kinases from diverse plants. Screening the 8k library with the active P2K1 kinase domain identified 177 phosphopeptides, including calcineurin B–like protein and G protein alpha subunit 1, which functions in cellular calcium signaling. We confirmed that P2K1 directly phosphorylates calcineurin B–like protein and G protein alpha subunit 1 through in vitro kinase assays. This expanded 8k KiC assay will be a useful tool for identifying novel substrates across diverse plant protein kinases, ultimately facilitating the exploration of previously undiscovered signaling pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mast1 mediates radiation-induced gastric injury via the P38 MAPK pathway

Radiation-induced gastric injury is a serious adverse effect and reduces the efficacy of radiotherapy treatment. However, the mechanisms underlying radiation-induced stomach injury remain unclear. Here, mouse stomach and gastric epithelial cells were irradiated with different doses of X-ray radiation. The results showed that radiation induced gastric injury in vivo and in vitro. Differentially expressed functional mRNAs in irradiation-induced gastric tissues were screened from the Gene Expression Omnibus (GEO) database. We found that the expression of microtubule-associated serine/threonine kinase 1 (Mast1) was downregulated in mouse gastric tissues and gastric epithelial cells after irradiation. Furthermore, functional assays showed that knockdown of Mast1 inhibited growth and promoted apoptosis in gastric epithelial cells, while overexpression of Mast1 protected gastric epithelial cells from radiation damage. Mechanistically, Mast1 negatively regulated radiation-induced injury in gastric epithelial cells by inhibiting the activation of P38. The apoptosis caused by knockdown of Mast1 in gastric epithelial cells could be partially reversed by the P38 inhibitor SB203580. Moreover, data from several gastric cancer cell lines and online databases revealed that Mast1 was not involved in the development of gastric cancer. Collectively, our findings demonstrated that Mast1 is essential for radiation-induced gastric injury, providing a promising prognostic and therapeutic target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Oxygenation influences xylose fermentation and gene expression in the yeast genera Spathaspora and Scheffersomyces

Abstract Background Cost-effective production of biofuels from lignocellulose requires the fermentation of d -xylose. Many yeast species within and closely related to the genera Spathaspora and Scheffersomyces (both of the order Serinales) natively assimilate and ferment xylose. Other species consume xylose inefficiently, leading to extracellular accumulation of xylitol. Xylitol excretion is thought to be due to the different cofactor requirements of the first two steps of xylose metabolism. Xylose reductase (XR) generally uses NADPH to reduce xylose to xylitol, while xylitol dehydrogenase (XDH) generally uses NAD + to oxidize xylitol to xylulose, creating an imbalanced redox pathway. This imbalance is thought to be particularly consequential in hypoxic or anoxic environments. Results We screened the growth of xylose-fermenting yeast species in high and moderate aeration and identified both ethanol producers and xylitol producers. Selected species were further characterized for their XR and XDH cofactor preferences by enzyme assays and gene expression patterns by RNA-Seq. Our data revealed that xylose metabolism is more redox balanced in some species, but it is strongly affected by oxygen levels. Under high aeration, most species switched from ethanol production to xylitol accumulation, despite the availability of ample oxygen to accept electrons from NADH. This switch was followed by decreases in enzyme activity and the expression of genes related to xylose metabolism, suggesting that bottlenecks in xylose fermentation are not always due to cofactor preferences. Finally, we expressed XYL genes from multiple Scheffersomyces species in a strain of Saccharomyces cerevisiae . Recombinant S. cerevisiae expressing XYL1 from Scheffersomyces xylosifermentans , which encodes an XR without a cofactor preference, showed improved anaerobic growth on xylose as the primary carbon source compared to S. cerevisiae strain expressing XYL genes from Scheffersomyces stipitis . Conclusion Collectively, our data do not support the hypothesis that xylitol accumulation occurs primarily due to differences in cofactor preferences between xylose reductase and xylitol dehydrogenase; instead, gene expression plays a major role in response to oxygen levels. We have also identified the yeast Sc. xylosifermentans as a potential source for genes that can be engineered into S. cerevisiae to improve xylose fermentation and biofuel production.

09 BIOMASS FUELS↗
DOE OSTI2024

A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on in vitro testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of phenolic antioxidant capacity in beverages based on laccase immobilized on screen-printed carbon electrode modified with graphene nanoplatelets and gold nanoparticles

A simple and highly sensitive electrochemical biosensor based on laccase immobilized onto a gold nanoparticles/graphene nanoplatelets-modified screen-printed carbon electrode (LACC/AuNP/GNPl/SPCE) was developed for the determination of hydroquinone (HQ) and other phenolic compounds. The biosensor shows excellent electro-catalytic activity towards oxidation of hydroquinone at a potential of -0.05 V (vs Ag/AgCl, 3 M KCl) in phosphate buffer as supporting electrolyte (0.1 M, pH 7.0) using hydrodynamic amperometry. Analytical characteristics uncover that the LACC/AuNP/GNPl/SPCE comprises a wide linear range for the dependence of the signal on HQ concentrations from 4 to 130 µM with a detection limit (3σ) of 1.5 µM. The repeatability (5 measurements, 100 µM hydroquinone) is ±2% and the reproducibility (5 biosensors, 100 µM hydroquinone) is ±3%. Interference studies of most common compounds with the determination of hydroquinone demonstrated negligible effects. Finally, the biosensor and the analytical method were applied to the determination of phenolic antioxidant capacity (AOC) in wine and blueberry syrup based on Trolox (6‑hydroxy‑2,5,7,8-tetramethylchromane-2-carboxylic acid) and hydroquinone equivalents. The results were evaluated by using their calibration curves which were satisfactory and agreed well with the results obtained by the reference method Trolox Equivalent Antioxidant Capacity assay (TEAC-Assay).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Delivered complementation in planta (DCIP) enables measurement of peptide-mediated protein delivery efficiency in plants

Abstract Using a fluorescence complementation assay, Delivered Complementation in Planta (DCIP), we demonstrate cell-penetrating peptide-mediated cytosolic delivery of peptides and recombinant proteins in Nicotiana benthamiana. We show that DCIP enables quantitative measurement of protein delivery efficiency and enables functional screening of cell-penetrating peptides for in-planta protein delivery. Finally, we demonstrate that DCIP detects cell-penetrating peptide-mediated delivery of recombinantly expressed proteins such as mCherry and Lifeact into intact leaves. We also demonstrate delivery of a recombinant plant transcription factor, WUSCHEL (AtWUS), into N. benthamiana. RT-qPCR analysis of AtWUS delivery in Arabidopsis seedlings also suggests delivered WUS can recapitulate transcriptional changes induced by overexpression of AtWUS. Taken together, our findings demonstrate that DCIP offers a new and powerful tool for interrogating cytosolic delivery of proteins in plants and highlights future avenues for engineering plant physiology.

59 BASIC BIOLOGICAL SCIENCES↗